This disclosure relates generally to robotic workcells and more specifically to an automated robot teach tool that enables a robot to automatically program all of the pick and place positions associated with a robotic workcell without robot operator intervention.
One of the most time-consuming and arduous aspects of setting up a robotic workcell is programming all of the robot's pick and place positions. A large automated cell could have dozens of points that must be manually taught. The operator, by using various buttons on a teach pendant, that typically takes the form of a hand-held device, can move a robot's end effector through six degrees of freedom to align the end effector within an acceptable tolerance to a given pick/place position. This process is repeated for each position. The speed and accuracy of this operation is subject to many factors including experience, fatigue, and visual acuity of the robot operator. Other factors that affect the speed and accuracy of the teaching operation include the ability of the robot operator to view a given pick/place point up close and from beneficial orientations, and room lighting in which the robot is taught.
The nature of this type of manual teaching operation means that some points will not be taught as well as others. As a result, some robot picks or places may be “rough” during operation of the robot. That is, the picked or placed object might hit, to varying degrees, a nearby surface on the way into or out of the taught point. Consequently, such taught points often need to be refined by the robot operator one or more times to increase the accuracy of the point.
The task of teaching points in a modular robotic workcell is exponentially more onerous. In a modular robotic workcell design, mobile, dockable carts are quickly and easily moved to and from robotic workcells where various process operations are performed on workpieces or objects that are carried by these carts. A typical modular robotic workcell design can require a robot operator to teach hundreds of points, each of which can take anywhere from 10 to 30 minutes to teach. The result is that time spent initially teaching a modular workcell system can take anywhere from a few hours for a small, monolithic system, to a week or more for large, modular systems. Furthermore, this teaching is not a one-time operation. For example, if an end effector or robot becomes damaged and needs to be replaced, then the entire workcell must be retaught, which will take just as long and require as much effort as the initial teaching exercise.